Colonisation of hospital surfaces from low- and middle-income countries by extended spectrum β-lactamase- and carbapenemase-producing bacteria

Hospital surfaces can harbour bacterial pathogens, which may disseminate and cause nosocomial infections, contributing towards mortality in low- and middle-income countries (LMICs). During the BARNARDS study, hospital surfaces from neonatal wards were sampled to assess the degree of environmental surface and patient care equipment colonisation by Gram-negative bacteria (GNB) carrying antibiotic resistance genes (ARGs). Here, we perform PCR screening for extended-spectrum β-lactamases (blaCTX-M-15) and carbapenemases (blaNDM, blaOXA-48-like and blaKPC), MALDI-TOF MS identification of GNB carrying ARGs, and further analysis by whole genome sequencing of bacterial isolates. We determine presence of consistently dominant clones and their relatedness to strains causing neonatal sepsis. Higher prevalence of carbapenemases is observed in Pakistan, Bangladesh, and Ethiopia, compared to other countries, and are mostly found in surfaces near the sink drain. Klebsiella pneumoniae, Enterobacter hormaechei, Acinetobacter baumannii, Serratia marcescens and Leclercia adecarboxylata are dominant; ST15 K. pneumoniae is identified from the same ward on multiple occasions suggesting clonal persistence within the same environment, and is found to be identical to isolates causing neonatal sepsis in Pakistan over similar time periods. Our data suggests persistence of dominant clones across multiple time points, highlighting the need for assessment of Infection Prevention and Control guidelines.

The major strength of this study is the multi-national nature (10 hospitals from 6 LMIC countries), the first ever being done.However, there are many weaknesses that dampen the enthusiasm for this project.First, there is lack of consistency of which samples to be swabbed and the number of swabs performed per hospital.Second, water is found to harbor more bacteria with ARG, but when compared between hospitals, the rates of ARG of all sites are combined.Third, all samples from all swabs (including water) are combined together as environment when rate of ARG colonization is calculated (samples include hospital surfaces, patient equipment, G-tubes and Foley catheters, etc).These 3 weaknesses together render comparison of ARG rates between hospitals difficult.Fourth, the genetic relatedness between isolates is poorly described.The number of clinical isolates (denoted as sepsis isolates) are not clearly stated.Although SNP distance is given, a phylogenetic tree comparison between strains might provide a better visualization.Furthermore, since Nanopore sequencing is performed, are the authors able to compare the genetic relationship between plasmids (to suggest horizontal plasmid spread among different species)?Lastly, this is merely a descriptive study, and heavy colonization with ARG GNB has been previously described for LMIC single hospital -thus this study is not original.

Other comments:
Lines 64-66 -sentence needs to be rewritten Lines 183-188 -are the same items swabbed between different timepoints?Some items might be more colonized than the others Lines 200-210, Figure 2 and Table S4c -Are different species recovered from different swab sites?In another word, are Pseudomonas aeruginosa more prominent from water?Stratifying species per swab sites might be important Table S7 -difficult to understand 1) abbreviations are not spelled out; 2) what is original versus corrected surfaces?3) What is N/A?If this reflects not done, why positive or negative PCR result is denoted?4) Why Foley catheter and G-tube are included in environmental sampling?Table S3.The total number does not add up (number in individual cell from columns C to H added together is less than number in column I) -See examples in rows 38, 40 etc.
Reviewer #2 (Remarks to the Author): "Colonisation of extended spectrum β-lactamase-and carbapenemase-producing bacteria on hospital surfaces from low-/middle-income countries" by Nieto-Rosado and colleagues describes a large collection of samples from the hospital environment.6,290 environmental swabs (from multiple countries and hospitals) were taken and 3,816 of them grew Gram-neg organisms.Of those 13.3% were blaCTX-M-15+, 5.4% were blaNDM+ and 1.2% were bla-OXA48+.Some fraction of those drug resistant organisms were sequenced and clustered into putative transmission clusters with a small collection of neonatal-sepsis isolates.Low SNP counts between isolates (1-10) support transmission across surfaces and, potentially, to patients.This study will be of interest to clinicians in low-and middle-income countries, where the sampling was carried out, as it reports on important organisms and resistance genes in those countries and their prevalence on surfaces.Healthcare systems in high-income countries, where it can be difficult to get this sort of sampling access, should also take note of the shear number of surfaces that may harbor cultivatable organisms.The study is a considerable amount of work spanning a number of contries and healthcare systems.The authors have done a nice job of organizing a large amount of data in the supplementary tables.
1.The manuscript is extremely number heavy and, at times, it feels like the authors are simply reading the tables.For instance, in the first paragraph of the results it isn't necessary to show the math for every percentage "n=1,487/6,290 (23.6%)".It is also redundant with Table 1.I would scan the paper for places where large blocks of number-heavy text can be simplified.The paper is very descriptive.
2. There are a lot of p-values throughout the manuscript, including one stuck at the bottom of Table 1 but it was unclear to me what statistical test was being used and what data were being tested (e.g., Table 1).The methods mention Chi-squared test but that's it.Please be more explicit in the text and legends about what statistical tests are being run and how they should be interpreted.
3. Given the importance of the SNP calling, I would like to see more details in the methods instead of just referencing Sands et al and Carvalho et al It doesn't have to be extensive but a brief summary is needed.
1. First, there is lack of consistency of which samples to be swabbed and the number of swabs performed per hospital.We do agree with the reviewer here, and have pointed this out as a limitation of the study as it was extremely difficult to standardise swabbing on occasion during the study, and there was a variation in the outlay of the hospital wards throughout the BARNARDS network.Accordingly, we were cautious with our interpretation of the data and we therefore did not study correlation between Gram-negative bacteria (GNB) growth and/or antibiotic resistance gene (ARG) prevalence per surface type or per each of the hospital sites.We do plan to address this limitation in the next phase of BARNARDS, which will commence towards the end of 2023.
2. Second, water is found to harbour more bacteria with ARG, but when compared between hospitals, the rates of ARG of all sites are combined.We apologise for the confusion regarding the "water samples".We collected charcoal swabs with a label indicating the swab originated near a water source but no further information was provided (e.g., samples labelled as "tap water", and therefore it was classified under the category sinks and water system).As the term for the category leads to confusion, we have amended the text accordingly to clarify this category (please refer to a similar comment from reviewer 2, comment 15).We agree that the correlation between GNB growth and/or ARG prevalence per each surface type and per each country/hospital would have been a preferred analysis to observe whether certain surfaces are more contaminated in a hospital.Unfortunately, the limitations within the study (sampling consistency) prevented analysis on the country/site level in this case and therefore we have combined these data.Following categorisation into six surface categories (600-700 sample average per category, Supplementary Table S10 [S8 in submission]), our analysis permitted us to determine which surfaces were colonised with ARG carrying-bacteria but not per hospital site.We appreciate this comment, and have accordingly created an additional Supplementary Table (new S5) presenting ARG rates per surface category, and also per hospital site and country.We are aware that the results are not significant because of the sample number limitation per site, and we have clearly stated this in the article.The text has been amended accordingly to incorporate this into, the limitation section in the discussion.
3. Third, all samples from all swabs (including water) are combined together as environment when rate of ARG colonization is calculated (samples include hospital surfaces, patient equipment, G-tubes and Foley catheters, etc).We appreciate the umbrella use of the term "environment" might be confusing; however, we have considered all hospital surfaces as "environmental" in the hospital/clinical context for this manuscript.Please, see comment 8d).In relation to a previous comment, we have added descriptive details and frequencies regarding ARG colonisation per each surface category (new S5); and Supplementary Table S4 shows ARG per surface type.

These 3 weaknesses together render comparison of ARG rates between hospitals difficult.
We agree with this summary and these sampling limitations have prevented detailed hospital/country-level analysis.Nevertheless, this is a very large dataset that will add considerable emphasis to otherwise scant data on the topic of infection prevention and control (IPC).We hope that this data will bring some much needed attention on IPC in many LMIC sites (a key topic tabled for the UN AMR high level meeting in 2024), regarding the amount of GNB growth found in hospitals and associated ARGs.We hope that this dataset will emphasise that the importance of cleaning hospital surfaces can aid in informing future IPC practices.We are looking forward to building on this study during our next phase of the BARNARDS project, with more standardised sampling allowing prevalence to be assessed per hospital site.. b.Although SNP distance is given, a phylogenetic tree comparison between strains might provide a better visualization.We appreciate that phylogenetic trees allow better visualisation of larger clusters, particularly ST15 K. pneumoniae.However, we have opted to include a figure that summarises multiple STs/bacterial isolates (Figure 4 for resubmission, submitted as Figure 3) instead of creating phylogenetic trees for this article.Please also note that many clusters are quite small, which would limit the impact of a phylogenetic tree, and, for ST15 K. pneumoniae, there is an additional dataset linked to samples collected from the mother and neonatal rectal samples (DOI: 10.1038/s41564-022-01184-y) that will be soon submitted for publication elsewhere and includes larger phylogenetic trees.
c. Furthermore, since Nanopore sequencing is performed, are the authors able to compare the genetic relationship between plasmids (to suggest horizontal plasmid spread among different species)?
We thank the reviewer for this suggestion -we have performed additional analysis to incorporate plasmid analysis and genetic relationships between plasmids where appropriate, using available clinical and metadata to suggest whether there is evidence to support horizontal plasmid transfer.Please see section 2.5 and the addition of a new main figure, Figure 3 -a Sankey diagram detailing information regarding linkage between carbapenemase gene variants and plasmid incompatibility groups.Furthermore, a comprehensive analysis of plasmid sequences (assemblies generated during whole genome assembly as outlined in the methods) has been summarised as a separate document called Supplementary Dataset 1.
Lastly, this is merely a descriptive study, and heavy colonization with ARG GNB has been previously described for LMIC single hospital -thus this study is not original.We acknowledge that the bulk of the data presented within this manuscript is descriptive.However, further to a comprehensive literature search, there are no other studies undertaken on multinational (13 sites and 8 counties) scale linking bacterial colonisation on hospital surfaces of AMR bacteria correlating with neonatal sepsis.We believe this study showcases the global issues and prevalence of ARGs.An important benefit of this study is the unified microbiology culture of samples from each hospital which allows aggregated data analysis across the BARNARDS network.The additional genomics analysis (in response to your earlier comment) further provides evidenced novelty within this manuscript.We highlight a large diversity of strains, and whilst the microbiology data alone is not novel, the addition of longread sequencing on this scale has allowed us to compare plasmids and identify cases of both clonal spread of bacterial strains across hospital surfaces, as well as cases of potential plasmid transfer between bacterial species.We would like to thank the reviewer for their comment in relation to the plasmid analysis, as we believe this has improved the quality of our analysis.In totality, our data summarises clear evidence that access to IPC measures is essential to limit transmission of AMR bacteria.We have added and edited the discussion around the impact of our data to lines 348-351 from the revised manuscript 2-9 .
5. Other comments: Lines 64-66 -sentence needs to be rewritten We thank the reviewer for this feedback, we have now amended these lines.
6. Lines 183-188 -are the same items swabbed between different timepoints?Some items might be more colonized than the others We thank the reviewer for raising this point.This analysis is a pooled data, and whilst some items are swabbed at different timepoints, this was not strictly specified during sampling.We agree we cannot assume there is a correlation between ARG prevalence and certain time points.Bacterial colonisation likely depends on multiple factors including the type of surface and, our sampling limitations prevents answering this query more fully.However, we do state that ARGcarrying bacteria are more frequently detected in HSS collected between March and October (lines 367-369 in submitted manuscript); and consequently, we have acknowledged that "Due to inconsistent sampling among time periods, seasonal analysis per country was not performed."We have amended lines 187-188 in the submitted manuscript (lines 176-177 in the revised version).We agree with the hypothesis that highly contaminated surfaces may have been swabbed more often during these time episodes.Our aim, with this analysis, was to highlight certain patterns of clonal prevalence and state any observed differences between time bands throughout the study period.We did not aim to specifically correlate colonisation to months of the year, and our analysis is exploratory in nature.We considered existing differences not only in type of surfaces collected, but also in seasons between countries and even areas within the same country (e.g.seasons in Cape Town and the rest of South Africa are different).We did not make prevalence comparisons between seasons or times of the year, and per hospital/country.We have amended the text, e.g.submitted lines 368-369, and limitations (linked to comment 2).
7. Lines 200-210, Figure 2 and Table S4c -Are different species recovered from different swab sites?In another word, are Pseudomonas aeruginosa more prominent from water?Stratifying species per swab sites might be important We agree with the reviewer's suggestion and carbapenemase-carrying bacterial species are stratified per hospital site in Supplementary Table S6 (submitted as S4), so the reader can observe the bacterial species recovered in each hospital site.Because of our main limitation with the swabbing, we cannot state that a specific bacterial species was more frequently found in one hospital site or surface category (explanation in comment 1-3).Moreover, in this study we screened for the presence of ESBL or carbapenemase ARGs within the bacterial species colonising the hospital surfaces rather than delineating the bacterial profile.Due to our approach, we are unable to accurately determine whether P. aeruginosa or any other bacterial species is more frequently found in a specific surface within a hospital, and that is fundamentally why Supplementary Table S6 shows bacterial species recovered per hospital site and not per surface category.Additionally, this is the reason why surface category was considered for potential transmission conclusion (Figure 4) and not for correlation with bacterial species.In the discussion section (lines 351-354 and lines 356-358 from the submitted manuscript), we did not make any correlation between bacterial species and surface type or category.Therefore, we have stated that "recovery from HSS", "surfaces in the ward", or "multiple clusters detected from hospital surfaces".We agree that analysing between bacterial species versus surface category is important when considering environmental reservoirs in the hospital settings to understand if certain surfaces pose a higher threat to patients/outbreaks if a particular species is found in a particular environment.Supplementary Table S7 has been created for this resubmission, which shows n (%) of bacterial species and isolates carrying blaNDM and blaOXA-48-like per surface category.We anticipate that our next phase of BARNARDS will fully address this research question.
We thank the reviewer for this feedback and have modified the table accordingly.a. 1) abbreviations are not spelled out; these are now all added in Supplementary Table S10 (submitted as S7) b.
2) what is original versus corrected surfaces?This has been addressed and identified by both reviewers, please see a detailed response in comment 19 from reviewer 2. c. 3) What is N/A?If this reflects not done, why positive or negative PCR result is denoted?N/A means PCR was not performed for those samples with no growth (N) on VC (NA for blaCTX-M-15 screening) or for VE (NA for carbapenemase genes).d. 4) Why are Foley catheter and G-tube included in environmental sampling?
We have added text for clarity in the methods, and results/discussions as appropriate (please also see comments 15 and 16 from reviewer 2).Gastrostomy tubes or "feeding tubes" (as reported by the hospital sites), as well as foley catheter, were included within the medical equipment category.According to the first definition used in our methods section, we collected hospital surface swabs (HSS).However, the terms "environmental surfaces and patient care equipment" have been used in the discussion, following CDC guideline definitions 10 .In methods we used the terms "medical equipment and inanimate surfaces", following WHO definitions 5,8,11 considered to be equally used for surfaces surrounding the patient immediate surroundings.The use of "inanimate" has been eliminated from the paper.Terms will be used according to CDC guidelines 10 throughout the paper: environmental surfaces (e.g., bed, cot, bed rails, mattresses) and patient care equipment (also described in this work as medical equipment or mobile medical equipment, including non-critical, semi-critical and noncritical patient care equipment) have been clarified in the methods section.Creating the two categories "medical equipment" and "mobile medical equipment" allowed us to distinguish between patient care equipment dedicated to a patient (direct patient care), and equipment moving across wards used for different patients.To conclude, feeding tubes and foley catheter would have been included within critical patient care equipment, as these devices enter sterile tissue or the vascular system.Being aware of this, these are classified under the umbrella of "patient care equipment" or, as defined in this manuscript, "medical equipment".
9. Table S3.The total number does not add up (number in individual cell from columns C to H added together is less than number in column I) -See examples in rows 38, 40 etc.We thank the reviewer for noting the differences in numbers and we understand the difficulty with the number changes throughout the manuscript.As outlines in the submitted Table S3 (S4 in resubmission) caption "The total number of samples collected per individual surface (over 4,126) was used as denominator to calculate the prevalence of each ARG per each individual surface".Also, the second column (column I in the submitted S3) shows the number of samples collected per type of surface (total of 4,126).This column might be not adding up with the ARGs counts since more than one PCR reaction was performed on the 4,126 samples (samples might have been positive for more than one ARG).Table and caption have been amended to avoid confusion.

Reviewer #2 (Remarks to the Author):
"Colonisation of extended spectrum β-lactamase-and carbapenemase-producing bacteria on hospital surfaces from low-/middle-income countries" by Nieto-Rosado and colleagues describes a large collection of samples from the hospital environment.6,290 environmental swabs (from multiple countries and hospitals) were taken and 3,816 of them grew Gram-neg organisms.Of those 13.3% were blaCTX-M-15+, 5.4% were blaNDM+ and 1.2% were bla-OXA48+.Some fraction of those drug resistant organisms were sequenced and clustered into putative transmission clusters with a small collection of neonatal-sepsis isolates.Low SNP counts between isolates (1-10) support transmission across surfaces and, potentially, to patients.This study will be of interest to clinicians in low-and middle-income countries, where the sampling was carried out, as it reports on important organisms and resistance genes in those countries and their prevalence on surfaces.Healthcare systems in high-income countries, where it can be difficult to get this sort of sampling access, should also take note of the shear number of surfaces that may harbour cultivatable organisms.The study is a considerable amount of work spanning a number of countries and healthcare systems.The authors have done a nice job of organizing a large amount of data in the supplementary tables.
10.The manuscript is extremely number heavy and, at times, it feels like the authors are simply reading the tables.For instance, in the first paragraph of the results it isn't necessary to show the math for every percentage "n=1,487/6,290 (23.6%)".It is also redundant with Table 1.I would scan the paper for places where large blocks of number-heavy text can be simplified.The paper is very descriptive.We thank the reviewer for highlighting how number intensive the results section is and the manuscript text has been reduced and edited as suggested during this revision, including the removal of numbers that replicate data presented in Table 1.1).The methods mention Chi-squared test but that's it.Please be more explicit in the text and legends about what statistical tests are being run and how they should be interpreted.We thank the reviewer for highlighting a shortage of information about statistical tests and results.The methods section has been amended (line 546-552 for submission, 526-531 for revised version) and we have edited Table 1, 2 and 3 legends (Tables 1,3,4 for resubmission).P-values throughout the manuscript have been complemented with more details regarding the test and variables comparison performed.For instance, line 109-113 in submitted manuscript.
12. Given the importance of the SNP calling, I would like to see more details in the methods instead of just referencing Sands et al and Carvalho et al.It doesn't have to be extensive but a brief summary is needed.
We agree and apologise for the oversight and have added some details.

Minor points
13. * Title -Consider rewording to: "Colonisation of hospital surfaces from low-/middleincome countries by extended spectrum β-lactamase-and carbapenemase-producing bacteria" We appreciate the suggestion and we have changed the title accordingly.15. * Line 48 -throughout, it would be good to make sure you are differentiating sinks, drains, etc... from clean water and taps."water system" isn't very informative (see also lines 162, 165, 420) "Sinks and water system" has been changed to "surfaces near the sink drain".This term has been described in methods (together with 8d) and includes sink basin, faucet, faucet handles, and surrounding countertop.This term has been adopted from CDC reported evidence of sinks and other drains which may easily become contaminated with multidrugresistant organisms (MDRO) 12,13 , which can persist for a long period and are often difficult to remove, especially when IPC practices are limited 12,13 .Reducing healthcare-associated infections (HAIs) is included in the WHO action plan 14 , and CDC recommends reducing risk from water (including the term surfaces near the drain) as healthcare environmental infection prevention measure, and in this manner to prevent HAIs 12,13 .Due to limited information on sampling, HSS collected from surfaces near the sink drain were classified together.
16. * Throughout, the authors refer to surfaces as "inanimate" or "inert".I'm not sure what is supposed to be communicated by that."Fomite" would be the correct technical term.This might be less confusing given that some of the items (e.g., carts/trolleys) while not "animate" are mobile and can potentially be vectors for organisms to travel around.It also doesn't really cover things like various people's "hands" in table S3; are those really inanimate or HSS?We thank the reviewer for raising this concern.We have eliminated the use of inanimate throughout the manuscript (see comment 8d).In relation to healthcare workers hands (e.g.baby guardian, clinician, doctor, nurse, cleaner), as well as mother hand, these samples have been considered environmental surfaces and have been classified in patient zone.Surfaces in the patient zone are contaminated by bacteria colonising/infecting patients 7- 11,15 in two ways: direct shedding from patients and via healthcare workers hands 16 .According to CDC guideline best practices , the role of environmental surfaces, environmental cleaning but also hand hygiene play a role in the contact transmission pathway and in breaking the chain of this transmission.Contaminated hands of healthcare personnel can contaminate environmental surfaces unless proper hand hygiene and environmental cleaning are properly performed to prevent MDRO transmission to susceptible patients or their immediate surrounding.According to the Hand Hygiene Technical Reference Manual 17 , it is possible to prevent HAIs caused by cross-transmission via hands if hand hygiene is correctly followed.At the same time, cross-transmission could potentially happen by contamination of healthcare personnel from hand contact with contaminated environmental surfaces, patient care equipment, or patients 18 .Thus, healthcare workers hands, as well as mother hands, can act as reservoirs and could potentially contribute to cross-transmission when providing direct and indirect care.To avoid confusion for the reader, this point has been clarified in methods, together with other terms amended (comments 8d) and 15).
17. * Line 83 -"Outbreaks caused by carbapenem-resistant and hypervirulent K. pneumoniae have been reported."Sentence needs a reference or something.It seems out of place.We thank the reviewer for this feedback.We have now amended the text and added references.This text has been moved to discussion (line 344).
18. * Figure 1 legend is too wordy We thank the reviewer for this observation.Figure 1 caption has been reduced.
19. * Line 183 -"309 original individual surfaces".What is meant here by "original" The use of "original" in this way refers to the surface label provided before extended data cleaning and aggregation into categories.We used "original" to refer to the 309 different HSS collected "initially" by the hospital sites, and to differentiate them from the categories created.We have now amended the text for clarity and have eliminated the terms "original" and "individual" (line 183 in submitted manuscript, Supplementary Table S10 (submitted as S7) and Supplementary Table S4).
* Thank you for including the BioProject and genome accessions.They don't appear to be accessible/released but I assume that they will be on publication.We thank the reviewer for highlighting this, all data is now in the public domain.

ADDITIONAL COMMENTS FROM AUTHORS:
• After reanalysis in section 2.5 (comment 4, reviewer 1) we identified that the total number of isolates carrying blaOXA-48-like was 17 and not 18.This was likely an Error in Microsoft Excel sorting and has now been corrected.• As new figures and supplementary material was created, the supplementary information has also been amended.• During revision it was necessary to add new references.All new references are citated below for information:

14 .
* Line 102 -HSS define first useWe have checked for the first use of the abbreviations during revision.

11 .
There are a lot of p-values throughout the manuscript, including one stuck at the bottom of Table 1 but it was unclear to me what statistical test was being used and what data were being tested (e.g., Table